scholarly journals Solar Energy Potential in Kathmandu Valley, Nepal

2016 ◽  
Vol 8 (1) ◽  
pp. 77-82 ◽  
Author(s):  
Santosh Regmi ◽  
Sunil Adhikary
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Winter Season ◽  
Kathmandu Valley ◽  
Energy Potential ◽  
Solar Electricity

Meteorological data such as solar radiation (1975-1984, and 2002-2010) and sunshine duration (1968-2004) were analyzed to study temporal characteristics of solar energy and investigate solar energy potential in Kathmandu valley. Pre-monsoon and post monsoon seasons have higher mean monthly sunshine duration (about 8 hours/day) than summer (about 5 hours/day) and winter (about 7 hours/day) seasons over Kathmandu. Pre-monsoon and monsoon seasons receive solar energy of about 190 Wm-2 and 170 Wm-2 respectively. The winter season receives the least amount of solar radiation (135 Wm-2). Approximately 220 MW of solar electricity can be produced in Kathmandu that will substantially fulfill current energy demand and reduce environmental pollution in the valley by replacing fossil fuels with clean solar electricity.Journal of Hydrology and Meteorology, Vol. 8(1) 2012, p.77-82

scholarly journals Global solar radiation modeling using different machine learning and empirical models in Northeast China

2021 ◽  
Author(s):  
Yue Jia ◽  
Yongjun Su ◽  
Fengchun Wang ◽  
Pengcheng Li ◽  
Shuyi Huo
Keyword(s):  
Machine Learning ◽  
Solar Radiation ◽  
Solar Energy ◽  
Northeast China ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Learning Models ◽  
Machine Learning Models

Abstract Reliable global solar radiation (Rs) information is crucial for the design and management of solar energy systems for agricultural and industrial production. However, Rs measurements are unavailable in many regions of the world, which impedes the development and application of solar energy. To accurately estimate Rs, this study developed a novel machine learning model, called a Gaussian exponential model (GEM), for daily global Rs estimation. The GEM was compared with four other machine learning models and two empirical models to assess its applicability using daily meteorological data from 1997–2016 from four stations in Northeast China. The results showed that the GEM with complete inputs had the best performance. Machine learning models provided better estimates than empirical models when trained by the same input data. Sunshine duration was the most effective factor determining the accuracy of the machine learning models. Overall, the GEM with complete inputs had the highest accuracy and is recommended for modeling daily Rs in Northeast China.

scholarly journals Solar Radiation: Models and Measurement Techniques

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
C. K. Pandey ◽  
A. K. Katiyar
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Measurement Techniques ◽  
Research Work ◽  
Diffuse Radiation ◽  
Geometrical Parameters ◽  
Efficient Utilization ◽  
Energy Potential

In order to grasp the significance of the work accomplished by the author, it is necessary to keep abreast of the present developments in this field. The research work reported in the paper is an attempt to get knowledge to assess the solar energy potential for practical and efficient utilization in India. Our work is centered on estimating realistic values of solar (global and diffuse) radiation on horizontal and tilted surfaces using measured meteorological data and geographical and geometrical parameters for India.

Models for Determination of Solar Energy Potential

2008 ◽  
Vol 26 (5) ◽  
pp. 281-292 ◽  
Author(s):  
Kadir Bakirci
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Global Radiation ◽  
Statistical Error ◽  
Mean Bias Error ◽  
Bias Error ◽  
Energy Potential ◽  
Monthly Average ◽  
Correlation Models

Many solar energy systems require monthly average meteorological data as a basis for design. In the study, it was investigated whether existing solar radiation models are suitable to determine the values of solar radiation, and new empirical equations were developed which correlate the monthly average daily global radiation using sunshine hour data. The correlation models were compared by using statistical error tests such as mean bias error (MBE) and root mean square error (RMSE). The new correlation models demonstrate close agreement with the observed data. An application of this study was performed using the experimental data measured for Erzurum, Turkey.

scholarly journals Evaluation of distributional solar radiation parameters of Cacak using long-term measured global solar radiation data

2007 ◽  
Vol 11 (4) ◽  
pp. 125-134 ◽  
Author(s):  
Snezana Dragicevic ◽  
Nikola Vuckovic
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Demand ◽  
Energy Production ◽  
Global Solar Radiation ◽  
Primary Energy ◽  
Horizontal Surface ◽  
Energy Potential ◽  
Radiation Data

Serbia is becoming more dependent on imported primary energy to meet its increasing energy demand. The ratio of indigenous primary energy production to primary energy consumption is decreasing. Therefore, it is of great importance for Serbia to make use of its indigenous energy resources more effectively, including its solar energy potential. Knowledge of global solar radiation is essential in the prediction, study, and design of the economic viability of systems which use solar energy. In this paper, the solar radiation data on Cacak (lat 43.87?N, long 20.33?E) are analyzed based on 4 years of global solar radiation data measured on a horizontal surface. The distributional solar radiation parameters are derived from the available data and analyzed. The available solar radiation data on a horizontal surface are converted to that of various tilt angles and the yearly and monthly optimum tilt angles are determined.

Preliminary results on the determination of solar energy potential using LiDAR technology

2015 ◽  
Vol 6 (1) ◽  
pp. 11-17 ◽  
Author(s):  
G. Szabó ◽  
P. Enyedi ◽  
Gy. Szabó ◽  
I. Fazekas ◽  
T. Buday ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Production ◽  
Alternative Energy ◽  
Surface Model ◽  
Solar Panels ◽  
Energy Potential ◽  
Potential Surfaces ◽  
Large Power ◽  
Automatic Data

According to the challenge of the reduction of greenhouse gases, the structure of energy production should be revised and the increase of the ratio of alternative energy sources can be a possible solution. Redistribution of the energy production to the private houses is an alternative of large power stations at least in a partial manner. Especially, the utilization of solar energy represents a real possibility to exploit the natural resources in a sustainable way. In this study we attempted to survey the roofs of the buildings with an automatic method as the potential surfaces of placing solar panels. A LiDAR survey was carried out with 12 points/m2 density as the most up-to-date method of surveys and automatic data collection techniques. Our primary goal was to extract the buildings with special regard to the roofs in a 1 km2 study area, in Debrecen. The 3D point cloud generated by the LiDAR was processed with MicroStation TerraScan software, using semi-automatic algorithms. Slopes, aspects and annual solar radiation income of roof planes were determined in ArcGIS10 environment from the digital surface model. Results showed that, generally, the outcome can be regarded as a roof cadaster of the buildings with correct geometry. Calculated solar radiation values revealed those roof planes where the investment for photovoltaic solar panels can be feasible.

scholarly journals SOLAR ENERGY: A POTENTIAL SOURCE OF RENEWABLE AND CLEAN ENERGY

2018 ◽  
Vol 6 (8) ◽  
pp. 214-217
Author(s):  
Deepak Aryal
Keyword(s):  
Solar Energy ◽  
Urban Areas ◽  
Sunshine Duration ◽  
Winter Season ◽  
Clean Energy ◽  
Energy Utilization ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Solar Energy Utilization ◽  
Analytical Review

This paper reports analytical review results on the global and national importance of solar energy as a clean and renewable source of energy. Pre-monsoon and post monsoon seasons have higher mean monthly sunshine duration (about 8 hours/day) than summer (about 5 hours/day) and winter (about 7 hours/day) seasons in Kathmandu. The lowest sunshine duration during summer season is attributed to the effect of monsoonal clouds during that period. Pre-monsoon and monsoon seasons receive solar energy of about 250 W/m2 and 200 W/m2 respectively. The winter season receives the least amount of solar radiation (about 150 W/m2). Results show high prospect of solar energy utilization both in rural and urban areas of Nepal.

scholarly journals Effects of solar energy use on rural community: a study of Boyarjapha village in Paikgachha upazila

2020 ◽  
Author(s):  
Sajadul Alam Saimon ◽  
Rakibul Ahasan
Keyword(s):  
Solar Energy ◽  
Renewable Resources ◽  
Energy Demand ◽  
Energy Use ◽  
Solar Power ◽  
Working Hours ◽  
Remote Areas ◽  
Rural And Remote Areas ◽  
Solar Electricity ◽  
Day By Day

Renewable energy is of great importance for today’s world which is generally produced from natural sources. Countries like Bangladesh has to use this energy to meet their energy demand. Day by day the demand of electricity is increasing in stormy pace but our resource is limited. So using renewable resources i.e. solar power to meet the demand of electricity is highly necessary especially rural and remote areas. This paper examined the nature and extent of solar energy in Boyarjapha village of Paikgachha Upazila of Khulna district to analyse the effects of solar panel in their daily life. Many positive impacts of solar power were found out such as better quality lighting, education, entertainment, communications, business, increasing working hours, women empowerment, increasing awareness etc. There are a few bad effects of solar energy too. But Government intervention is a must to ensure better quality results in coming future. Similarly, government has to take serious steps to advertise solar electricity in remote areas of Bangladesh

Artificial Intelligence Techniques for Solar Energy and Photovoltaic Applications

2013 ◽  
pp. 376-436 ◽  
Author(s):  
Radian Belu
Keyword(s):  
Artificial Intelligence ◽  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Energy Systems ◽  
Poor Quality ◽  
Quality Of Data ◽  
Information Patterns ◽  
Time Requirements

Artificial intelligence (AI) techniques play an important role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms employed to model, control, or to predict performances of the energy systems are complicated involving differential equations, large computer power, and time requirements. Instead of complex rules and mathematical routines, AI techniques are able to learn the key information patterns within a multidimensional information domain. Design, control, and operation of solar energy systems require long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer of a number of shortcomings (e.g. poor quality of data, insufficient long series, etc.). To overcome these problems AI techniques appear to be one of the strongest candidates. The chapter provides an overview of commonly used AI methodologies in solar energy, with a special emphasis on neural networks, fuzzy logic, and genetic algorithms. Selected AI applications to solar energy are outlined in this chapter. In particular, methods using the AI approach for the following applications are discussed: prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.

Energy Demand, Availability in Nepal and Present PV Cost Analysis

Solar Energy ◽  
2005 ◽  
Author(s):  
Dilip C. Ghimire ◽  
Sudip Adhikari ◽  
Sunil Adhikary ◽  
Hideo Uchida ◽  
Masayoshi Umeno
Keyword(s):  
Solar Radiation ◽  
Energy Demand ◽  
Total Population ◽  
Maintenance Cost ◽  
Government Subsidy ◽  
Pv Module ◽  
Point Of Use ◽  
Generating Capacity ◽  
High Insulation ◽  
Solar Electricity

This paper describes the Photovoltaic solar electricity generating capacity in Nepal. Although Nepal is rich in hydropower, currently only about 17% of the total population has access of electricity. The majority of the population who are living in the rural mountainous parts of Nepal is still deprived of electricity. The relatively high insulation throughout the year and geographical situation encourage for the development of PV energy in the country. The monthly mean solar radiation analysis shows that April and January receive the highest and the lowest solar radiation respectively. The PV installation rate has increased dramatically in the last five years due to relative decrease in PV module cost and government subsidy. PV technology is reliable because of its simplicity, extremely low maintenance cost and point-of-use installation possibility. The widespread use of PV will help to reduce CO2 emission and consequently contributes towards better environment.

Feasibility of Usage Possibility in Turkey of Solar Driven Ejector-Absorption Cooling System

Solar Energy ◽  
2004 ◽  
Author(s):  
Adnan So¨zen ◽  
H. Serdar Yu¨cesu
Keyword(s):  
Solar Energy ◽  
Cooling System ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Minimum Energy ◽  
Montreal Protocol ◽  
Coefficient Of Performance ◽  
Promising Alternative ◽  
Absorption Cooling ◽  
Yearly Average

It appears that solar assisted refrigeration systems are a promising alternative to the conventional electrical driven units. Their main advantages are the reduction of peak loads for electricity utilities, the use of zero ozone depletion impact refrigerants, the decreased primary energy consumption, and decreased global warming impact. In this study, we have investigated the possibility of using ejector-absorption cooling systems (EACS) in Turkey. In addition, this study determines whether or not required heat for generator of EACS can be obtained from solar energy in Turkey. There are two important reasons to explain the use of EACS in Turkey. One is that the production and use of the CFCs and HCFCs will be phased out according to Montreal Protocol. The second is that, in Turkey, solar energy potential is very high due to its location in the northern hemisphere with latitudes 36–42°N and longitudes 26–45°E, the yearly average solar radiation is 3.6 kWh/m2 day, and the total yearly radiation period is ∼2610 h. The radiation data and sunshine duration information collected since 2000 for 17 cities are used for analysis in different regions of Turkey. For maximum coefficient of performance (COPmax) conditions of EACSs operated with aqua-ammonia, it is found that required optimum collector surface area was defined by using the meteorological data. In addition since the system can be used throughout the year, required minimum energy for auxiliary heater was also calculated. It is shown that the heat gain factor (HGF) varies in the range from 0.5 to 2.68 for the all the seasons in the selected cities. The maximum HGF is 2.68 for Van in July. This study shows that there is a great potential for utilisation of solar cooling system for domestic heating/cooling applications in Turkey.

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